CN113057610A - Dynamic blood pressure measurement calibration method and device of wearable equipment and storage medium - Google Patents
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Abstract
The invention discloses a dynamic blood pressure measurement calibration method of wearable equipment, which comprises the following steps: acquiring first measurement data measured by a medical standard sphygmomanometer and taking the first measurement data as standard data to acquire second measurement data measured by a blood pressure measurement module of the wearable equipment; performing discrete calculation on the second measurement data by taking the standard data as a datum point to obtain a current average value after the discrete calculation; calculating a current correction error parameter according to the average value; calculating the average value of the current correction error parameter and the last correction error parameter again to obtain a current effective correction error parameter; and correcting the blood pressure value measured by the wearable equipment by using the current effective correction error parameter. In addition, a dynamic blood pressure measurement calibration device of the wearable device and a storage medium are also provided. According to the technical scheme provided by the invention, the accuracy of dynamic blood pressure measurement of the wearable device is improved, and the risk of large error caused by blood pressure measurement of the wearable device is avoided.
Description
Technical Field
The invention relates to the technical field of dynamic blood pressure measurement of wearable equipment, in particular to a dynamic blood pressure measurement calibration method and device of wearable equipment and a storage medium.
Background
Along with intelligent wearing equipment's popularization, more and more old man is through wearing intelligent wearing equipment, like intelligent wrist-watch, the blood pressure change of mastering old man often through wearable equipment's dynamic blood pressure measurement. The blood pressure measurement of the wearable device is generally realized by a photoelectric sensor, a photoelectric sensor and electrocardio, an oscillography, an oximetry method and the like, the current blood pressure condition of the old can be checked in real time, and the blood pressure trend of the old can be further mastered by collecting the blood pressure change of the old; however, any blood pressure measurement method has the disadvantages of insufficient accuracy and large error, and blood pressure measurement completely depending on wearable equipment often causes misleading and results in loss of optimal treatment.
Disclosure of Invention
The invention provides a dynamic blood pressure measurement calibration method and device of wearable equipment and a storage medium, and aims to solve the problems of insufficient precision and large error of blood pressure measurement of the wearable equipment in the prior art.
In order to achieve the above object, the present invention provides a method for calibrating dynamic blood pressure measurement of a wearable device, comprising:
step S10: acquiring sleep finish time t1 of the old people acquired by the wearable device;
step S20: acquiring the current first measurement data measured by the medical standard sphygmomanometer and the measurement time t 2;
step S30: judging whether 1h > (t2-t1) >0 is met, if so, executing the step S40, otherwise, executing the step S10;
step S40: taking the first measurement data as standard data, and acquiring continuous multiple second measurement data measured by a blood pressure measurement module of the wearable device; the second measurement data is continuous multiple blood pressure measurement data of the wearable device within a preset time;
step S50: performing discrete calculation on the second measurement data by taking the standard data as a datum point, and calculating to obtain the average value after the discrete calculation;
step S60: calculating a current correction error parameter according to the average value;
step S70: calculating the average value of the current correction error parameter and the last correction error parameter again to obtain a current effective correction error parameter;
step S80: and correcting the blood pressure value measured by the wearable equipment by using the current effective correction error parameter.
Further, the step S50 includes:
step S510: performing discrete filtering on the second measurement data, and filtering out data with the maximum discreteness;
step S520: calculating discrete characteristics of the data subjected to discrete filtering by taking the standard data as a reference point;
step S530: and carrying out average value calculation on the second measurement data subjected to discrete characteristic calculation.
Further, the average value of this time is calculated as:
X′m＝(X1+X2+...Xm)/m
wherein:
X′mrepresenting the average value of the time;
X1to XmM second measurement data are represented, and m is a natural number.
Further, the discrete characteristic calculation includes that the second measurement data are distributed discretely on both sides of the reference point, on the left side of the reference point, and on the right side of the reference point.
Further, the calculation of the current correction error parameter in the step S60 is:
A′m＝(X′m-X0)/X′m
wherein the content of the first and second substances,
A′mrepresenting a current correction error parameter; m is a natural number;
X0representing standard data;
X′mthis average value is shown.
Further, the current valid correction error parameter is calculated as:
A″m＝(X′m-X′m-1)/2
wherein the content of the first and second substances,
A″mrepresenting a current valid correction error parameter; m is a natural number;
A′mrepresenting a current correction error parameter;
X′m-1representing the last corrected error parameter.
Further, the correction calculation in step S80 for correcting the blood pressure value measured by the wearable device using the current valid correction error parameter is:
Yn＝Xn*(1-A″m)
wherein the content of the first and second substances,
Ynindicating a correction value; n is a natural number;
Xnrepresenting the measured value;
A″mindicating the currently valid corrected error parameters.
Meanwhile, the invention also provides a device for calibrating the dynamic blood pressure measurement of the wearable device, which comprises a memory and a processor, wherein the memory stores a dynamic blood pressure measurement calibration program of the wearable device which can be operated by the processor, and the dynamic blood pressure measurement calibration program of the wearable device realizes the steps of the method for calibrating the dynamic blood pressure measurement of the wearable device when being executed by the processor.
In addition, the present invention also provides a storage medium, which is a computer-readable storage medium, and the storage medium stores thereon a dynamic blood pressure measurement calibration program of a wearable device, which is executable by one or more processors to implement the steps of the dynamic blood pressure measurement calibration method of a wearable device as described above.
According to the dynamic blood pressure measurement calibration method, device and storage medium of the wearable device, the accuracy of the dynamic blood pressure measurement of the wearable device is improved through automatic calibration of the dynamic blood pressure measurement of the wearable device, the risk of large errors caused by the blood pressure measurement of the wearable device is avoided, the dynamic blood pressure measurement data using the wearable device has high reference significance, the method and device are implemented noninductively for the old or the user, and the user experience is good.
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Fig. 1 is a schematic flowchart of a dynamic blood pressure measurement calibration method of a wearable device according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of step S50 in FIG. 1;
fig. 3 is a schematic view of an internal structure of a dynamic blood pressure measurement calibration apparatus of a wearable device according to an embodiment of the present invention;
fig. 4 is a schematic diagram of a dynamic blood pressure measurement calibration program module of a wearable device in a dynamic blood pressure measurement calibration apparatus of a wearable device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, an embodiment of the present invention provides a method for calibrating a dynamic blood pressure measurement of a wearable device, where the method for calibrating a dynamic blood pressure measurement of a wearable device includes:
step S10: acquiring sleep finish time t1 of the old people acquired by the wearable device;
step S20: acquiring the current first measurement data measured by the medical standard sphygmomanometer and the measurement time t 2;
step S30: judging whether 1h > (t2-t1) >0 is met, if so, executing the step S40, otherwise, executing the step S10;
step S40: taking the first measurement data as standard data, and acquiring continuous multiple second measurement data measured by a blood pressure measurement module of the wearable device; the second measurement data is continuous multiple blood pressure measurement data of the wearable device within a preset time;
step S50: performing discrete calculation on the second measurement data by taking the standard data as a datum point, and calculating to obtain the average value after the discrete calculation;
step S60: calculating a current correction error parameter according to the average value;
step S70: calculating the average value of the current correction error parameter and the last correction error parameter again to obtain a current effective correction error parameter;
step S80: and correcting the blood pressure value measured by the wearable equipment by using the current effective correction error parameter.
Specifically, the blood pressure of the elderly is measured, the blood pressure is stable within one hour of waking in sleep, and meanwhile, the wearable device can determine the sleep time of the elderly by measuring the change of data such as heart rate change, blood pressure change and the like of the elderly, and the sleep time of the elderly is within one hour (namely, 1h is satisfied) after the sleep end time t1>(t2-t1)>0) The first measurement data measured using the medical standard sphygmomanometer may be used as the standard data. Here, the wearable device is a smart watch, and meanwhile, the wearable device further has a communication module, the communication module includes bluetooth, WiFi, a mobile communication network (such as 4G, 5G, etc.), so that the wearable device is connected with a server, and data on the wearable device about the physical state of the elderly, such as heart rate, blood pressure data, etc., can be acquired in real time on the server. Therefore, a plurality of blood pressure measurement data of the wearable device within a preset time is acquired as the second measurement data, for example, every 5 minutes for 1 hour. Record the second measurement data as X1、X2、……、XmWherein m is a natural number; for example, every 5 minutes for 1 hour, there are 12 measurements. The second measurement data may be adjusted according to the length of the preset time and the length of the interval time, preferably, the preset time is 0.5-3 hours, and the interval time is 1 minute-30 minutes.
Referring to fig. 2, the step S50 includes:
step S510: performing discrete filtering on the second measurement data, and filtering out data with the maximum discreteness; further, since the data with the maximum discreteness may be interference data, the data with the maximum discreteness needs to be filtered out from the m second measurement data, where the data with the maximum discreteness may be 1 or more, and during calculation, the average value, the maximum value, the minimum value, and the discrete distribution of the m second measurement data are analyzed to find out the value with the maximum discrete number, where the value with the maximum discrete number includes a possible maximum value or a possible minimum value.
Step S520: calculating discrete characteristics of the data subjected to discrete filtering by taking the standard data as a reference point; the discrete characteristic calculation includes that the second measurement data are distributed discretely on both sides of the reference point, on the left side of the reference point and on the right side of the reference point.
Step S530: performing the average value calculation on the second measurement data subjected to the discrete characteristic calculation; specifically, the average value of this time is calculated as:
X′m＝(X1+X2+...Xm)/m
wherein:
X′mrepresenting the average value of the time;
X1to XmM second measurement data are represented, and m is a natural number.
The data with the largest discreteness among the m second measurement data is filtered by the discrete characteristic calculation, for example, the data with the error exceeding the set range (for example, the error exceeding 20%) of the measurement data is filtered as invalid data, and the filtered data is used as the second measurement data to calculate the average value this time.
Calculating a current correction error parameter according to the average value; the calculation of the current correction error parameter in step S60 is:
A′m＝(X′m-X0)/X′m
wherein the content of the first and second substances,
A′mrepresenting a current correction error parameter; m is a natural number;
X0representing standard data;
X′mthis average value is shown.
Calculating the average value of the current correction error parameter and the last correction error parameter again to obtain a current effective correction error parameter; the current effective correction error parameter is calculated as:
A″m＝(X′m-X′m-1)/2
wherein the content of the first and second substances,
A″mrepresenting a current valid correction error parameter; m is a natural number;
A′mrepresenting a current correction error parameter;
X′m-1representing the last corrected error parameter.
After the calculation of the current effective correction error parameter is completed, the current effective correction error parameter can be used for correcting the blood pressure measurement of the follow-up old people using the intelligent watch in real time. Specifically, the calculation of correcting the blood pressure value measured by using the wearable device using the current effective correction error parameter is as follows:
Yn＝Xn*(1-A″m)
wherein the content of the first and second substances,
Ynindicating a correction value; n is a natural number;
Xnrepresenting the measured value;
A″mindicating the currently valid corrected error parameters.
I.e. the blood pressure measurement value X of the n-th measurementnBy the currently valid correction error parameter A ″)mAfter correction, a correction value Y is obtainedn。
Therefore, the current effective correction error parameter is calculated by associating the current correction error parameter obtained last time with the current correction error parameter obtained last time, so that the error parameter distortion rate is reduced, and the correction accuracy rate is improved.
In addition, the invention also provides a dynamic blood pressure measurement and calibration device of the wearable device, and particularly the dynamic blood pressure measurement and calibration device of the wearable device is a host or a server for medical care, and can also be a mobile phone terminal and other devices for monitoring the blood pressure of the old.
Referring to fig. 3, an embodiment of the invention provides an internal structure diagram of a calibration apparatus for measuring dynamic blood pressure of a wearable device, where the calibration apparatus for measuring dynamic blood pressure of a wearable device at least includes a memory 11, a processor 12, a communication bus 13, and a network interface 14.
The memory 11 includes at least one type of readable storage medium, which includes a flash memory, a hard disk, a multimedia card, a card type memory (e.g., SD or DX memory, etc.), a magnetic memory, a magnetic disk, an optical disk, and the like. The memory 11 may in some embodiments be an internal storage unit of the ambulatory blood pressure measurement calibration device of the wearable device, e.g. a hard disk of the ambulatory blood pressure measurement calibration device of the wearable device. The memory 11 may also be an external storage device of the device for calibrating dynamic blood pressure measurement of the wearable device in other embodiments, such as a plug-in hard disk provided on the device for calibrating dynamic blood pressure measurement of the wearable device, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and so on. Further, the memory 11 may also comprise both an internal memory unit and an external memory device of the wearable device's ambulatory blood pressure measurement calibration apparatus. The memory 11 may be used to store not only application software installed in the ambulatory blood pressure measurement calibration apparatus of the wearable device and various types of data, such as codes of an ambulatory blood pressure measurement calibration program of the wearable device, but also temporarily store data that has been output or is to be output.
The processor 12 may be a Central Processing Unit (CPU), controller, microcontroller, microprocessor or other data Processing chip in some embodiments, and is used for running program codes stored in the memory 11 or Processing data, such as executing a dynamic blood pressure measurement calibration program of the wearable device.
The communication bus 13 is used to realize connection communication between these components.
The network interface 14 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface), and is typically used to establish a communication link between the ambulatory blood pressure measurement calibration device of the wearable device and other electronic devices; specifically, the dynamic blood pressure measurement calibration device of the wearable device is in communication connection with a wearable device (such as a smart watch) worn by an elderly person, and meanwhile, the dynamic blood pressure measurement calibration device of the wearable device can also be in communication connection with a medical standard sphygmomanometer to obtain the first measurement data.
Optionally, the device for calibrating dynamic blood pressure measurement of the wearable device may further include a user interface, the user interface may include a Display (Display), an input unit such as a Keyboard (Keyboard), and the optional user interface may further include a standard wired interface and a wireless interface. Alternatively, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch device, or the like. The display, which may also be referred to as a display screen or display unit, is suitable for displaying information processed in the ambulatory blood pressure measurement calibration device of the wearable device and for displaying a visual user interface.
Fig. 3 only shows the wearable device's dynamic blood pressure measurement calibration apparatus with the components 11-14 and the wearable device's dynamic blood pressure measurement calibration procedure, and it will be understood by those skilled in the art that the structure shown in fig. 3 does not constitute a limitation of the wearable device's dynamic blood pressure measurement calibration apparatus, and may include fewer or more components than those shown, or some components in combination, or a different arrangement of components.
In the embodiment of the device for calibrating dynamic blood pressure measurement of a wearable device shown in fig. 3, a memory 11 stores a program for calibrating dynamic blood pressure measurement of a wearable device; the processor 12, when executing the dynamic blood pressure measurement calibration program of the wearable device stored in the memory 11, implements the following steps:
step S10: acquiring sleep finish time t1 of the old people acquired by the wearable device;
step S20: acquiring the current first measurement data measured by the medical standard sphygmomanometer and the measurement time t 2;
step S30: judging whether 1h > (t2-t1) >0 is met, if so, executing the step S40, otherwise, executing the step S10;
step S40: taking the first measurement data as standard data, and acquiring continuous multiple second measurement data measured by a blood pressure measurement module of the wearable device; the second measurement data is continuous multiple blood pressure measurement data of the wearable device within a preset time;
step S50: performing discrete calculation on the second measurement data by taking the standard data as a datum point, and calculating to obtain the average value after the discrete calculation;
step S60: calculating a current correction error parameter according to the average value;
step S70: calculating the average value of the current correction error parameter and the last correction error parameter again to obtain a current effective correction error parameter;
step S80: and correcting the blood pressure value measured by the wearable equipment by using the current effective correction error parameter.
Referring to fig. 4, a schematic diagram of program modules of a dynamic blood pressure measurement calibration program of a wearable device in an embodiment of the dynamic blood pressure measurement calibration apparatus of a wearable device according to the present invention is shown, in this embodiment, the dynamic blood pressure measurement calibration program of the wearable device may be divided into an acquisition module 10, an acquisition module 20, a calculation module 30, and a calibration module 40, which exemplarily:
the acquisition module 10 is used for acquiring the sleep finish time t1 of the old people acquired by the wearable device;
an obtaining module 20, configured to perform obtaining first measurement data and second measurement data;
a calculation module 30 for performing a calculation of the average pitch;
and the calibration module 40 is used for performing calibration on the blood pressure value measured by using the wearable device by using the calibration coefficient.
The functions or operation steps of the acquisition module 10, the acquisition module 20, the calculation module 30, and the calibration module 40 implemented when the program modules are executed are substantially the same as those of the above embodiments, and are not repeated herein.
Furthermore, an embodiment of the present invention further provides a storage medium, where the storage medium is a computer-readable storage medium, and the storage medium stores a dynamic blood pressure measurement calibration program of a wearable device, where the dynamic blood pressure measurement calibration program of the wearable device is executable by one or more processors to implement the following operations:
step S10: acquiring sleep finish time t1 of the old people acquired by the wearable device;
step S20: acquiring the current first measurement data measured by the medical standard sphygmomanometer and the measurement time t 2;
step S30: judging whether 1h > (t2-t1) >0 is met, if so, executing the step S40, otherwise, executing the step S10;
step S40: taking the first measurement data as standard data, and acquiring continuous multiple second measurement data measured by a blood pressure measurement module of the wearable device; the second measurement data is continuous multiple blood pressure measurement data of the wearable device within a preset time;
step S50: performing discrete calculation on the second measurement data by taking the standard data as a datum point, and calculating to obtain the average value after the discrete calculation;
step S60: calculating a current correction error parameter according to the average value;
step S70: calculating the average value of the current correction error parameter and the last correction error parameter again to obtain a current effective correction error parameter;
step S80: and correcting the blood pressure value measured by the wearable equipment by using the current effective correction error parameter.
The embodiment of the storage medium of the present invention is substantially the same as the embodiments of the above wearable device dynamic blood pressure measurement calibration method and device, and will not be described herein again.
Compared with the prior art, the dynamic blood pressure measurement calibration method, the device and the storage medium of the wearable device provided by the invention have the advantages that the accuracy of the dynamic blood pressure measurement of the wearable device is improved through the automatic calibration of the dynamic blood pressure measurement of the wearable device, the risk of large errors caused by the blood pressure measurement of the wearable device is avoided, the dynamic blood pressure measurement data of the wearable device has higher reference significance, the method and the device are realized to the old or the user without sense, and the user experience is good.
It should be noted that the above-mentioned numbers of the embodiments of the present invention are merely for description, and do not represent the merits of the embodiments. And the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, apparatus, article, or method that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, apparatus, article, or method. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, apparatus, article, or method that comprises the element.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium (e.g., ROM/RAM, magnetic disk, optical disk) as described above, and includes instructions for enabling a terminal device (e.g., a drone, a mobile phone, a computer, a server, or a network device) to execute the method according to the embodiments of the present invention.
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (9)
1. A dynamic blood pressure measurement calibration method of a wearable device is characterized by comprising the following steps:
step S10: acquiring sleep finish time t1 of the old people acquired by the wearable device;
step S20: acquiring the current first measurement data measured by the medical standard sphygmomanometer and the measurement time t 2;
step S30: judging whether 1h > (t2-t1) >0 is satisfied, if so, executing step S40, otherwise, executing step S10;
step S40: taking the first measurement data as standard data, and acquiring continuous multiple second measurement data measured by a blood pressure measurement module of the wearable device; the second measurement data is continuous multiple blood pressure measurement data of the wearable device within a preset time;
step S50: performing discrete calculation on the second measurement data by taking the standard data as a datum point, and calculating to obtain the average value after the discrete calculation;
step S60: calculating a current correction error parameter according to the average value;
step S70: calculating the average value of the current correction error parameter and the last correction error parameter again to obtain a current effective correction error parameter;
step S80: and correcting the blood pressure value measured by the wearable equipment by using the current effective correction error parameter.
2. The method for calibrating the dynamic blood pressure measurement of a wearable device according to claim 1, wherein the step S50 comprises:
step S510: performing discrete filtering on the second measurement data, and filtering out data with the maximum discreteness;
step S520: calculating discrete characteristics of the data subjected to discrete filtering by taking the standard data as a reference point;
step S530: and carrying out average value calculation on the second measurement data subjected to discrete characteristic calculation.
3. The method for calibrating the dynamic blood pressure measurement of a wearable device according to claim 2, wherein the current average value is calculated as:
X′m＝(X1+X2+...Xm)/m
wherein:
X′mrepresenting the average value of the time;
X1to XmM second measurement data are represented, and m is a natural number.
4. The method of claim 2, wherein the discrete characteristic calculation comprises a discrete distribution of the second measurement data across, to the left of, and to the right of the reference point.
5. The method for calibrating the dynamic blood pressure measurement of a wearable device according to claim 1, wherein the calculation of the current correction error parameter in step S60 is:
A′m＝(X′m-X0)/X′m
wherein the content of the first and second substances,
A′mrepresenting a current correction error parameter; m is a natural number;
X0representing standard data;
X′mthis average value is shown.
6. The method for calibrating ambulatory blood pressure measurement of a wearable device according to claim 1, wherein the current valid correction error parameter is calculated by:
A″m＝(X′m-X′m-1)/2
wherein the content of the first and second substances,
A″mrepresenting a current valid correction error parameter; m is a natural number;
A′mrepresenting a current correction error parameter;
X′m-1representing the last corrected error parameter.
7. The method for calibrating the dynamic blood pressure measurement of a wearable device according to claim 1, wherein the correction calculation in step S80 for correcting the blood pressure value measured by the wearable device using the current valid correction error parameter is:
Yn＝Xn*(1-A″m)
wherein the content of the first and second substances,
Ynindicating a correction value; n is a natural number;
Xnrepresenting the measured value;
A″mindicating the currently valid corrected error parameters.
8. An apparatus for calibrating a dynamic blood pressure measurement of a wearable device, comprising a memory and a processor, wherein the memory stores a dynamic blood pressure measurement calibration program of the wearable device executable by the processor, and the processor executes the dynamic blood pressure measurement calibration program of the wearable device to implement the steps of the method for calibrating a dynamic blood pressure measurement of a wearable device according to any one of claims 1 to 7.
9. A storage medium, characterized in that the storage medium is a computer-readable storage medium, on which a dynamic blood pressure measurement calibration program of a wearable device is stored, the dynamic blood pressure measurement calibration program of the wearable device being executable by one or more processors to implement the steps of the dynamic blood pressure measurement calibration method of the wearable device according to any one of claims 1 to 7.
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Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH10151118A (en) * | 1996-11-22 | 1998-06-09 | Omron Corp | Electronic blood pressure gauge |
| DE102006051973A1 (en) * | 2006-11-03 | 2008-05-08 | Rossmax International Ltd. | Basal blood pressure measuring and displaying method for patient, involves displaying measured basal blood pressure and measurement date on display screen, and automatic storing of data set for measured basal blood pressure in memory |
| CN101190125A (en) * | 2006-11-27 | 2008-06-04 | 优盛医学科技股份有限公司 | Basic blood pressure measuring device |
| US20130041270A1 (en) * | 2011-08-08 | 2013-02-14 | Kuo-Yuan Chang | Blood pressure measuring device and system with automatic self-examination and self-calibration functions |
| CN203195675U (en) * | 2011-11-15 | 2013-09-18 | 西铁城控股株式会社 | Electronic sphygmomanometer |
| CN104188639A (en) * | 2014-09-10 | 2014-12-10 | 朱宇东 | Ambulatory blood pressure continuous monitoring and real-time analysis system |
| CN205514564U (en) * | 2016-01-28 | 2016-08-31 | 北京麦迪克斯科技有限公司 | Developments blood pressure check device |
| CN109893110A (en) * | 2019-03-06 | 2019-06-18 | 深圳市理邦精密仪器股份有限公司 | A kind of method and device for calibrating ambulatory blood pressure |
| CN110226926A (en) * | 2018-03-06 | 2019-09-13 | 罗伯特·博世有限公司 | For the calibration method of blood pressure device |
| CN112040854A (en) * | 2018-05-24 | 2020-12-04 | 欧姆龙健康医疗事业株式会社 | Blood pressure management device, blood pressure management method, and blood pressure management program |
| CN112274126A (en) * | 2020-10-28 | 2021-01-29 | 河北工业大学 | Noninvasive continuous blood pressure detection method and device based on multiple pulse waves |
-
2021
- 2021-02-07 CN CN202110174502.6A patent/CN113057610B/en active Active
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH10151118A (en) * | 1996-11-22 | 1998-06-09 | Omron Corp | Electronic blood pressure gauge |
| DE102006051973A1 (en) * | 2006-11-03 | 2008-05-08 | Rossmax International Ltd. | Basal blood pressure measuring and displaying method for patient, involves displaying measured basal blood pressure and measurement date on display screen, and automatic storing of data set for measured basal blood pressure in memory |
| CN101190125A (en) * | 2006-11-27 | 2008-06-04 | 优盛医学科技股份有限公司 | Basic blood pressure measuring device |
| US20130041270A1 (en) * | 2011-08-08 | 2013-02-14 | Kuo-Yuan Chang | Blood pressure measuring device and system with automatic self-examination and self-calibration functions |
| CN203195675U (en) * | 2011-11-15 | 2013-09-18 | 西铁城控股株式会社 | Electronic sphygmomanometer |
| CN104188639A (en) * | 2014-09-10 | 2014-12-10 | 朱宇东 | Ambulatory blood pressure continuous monitoring and real-time analysis system |
| CN205514564U (en) * | 2016-01-28 | 2016-08-31 | 北京麦迪克斯科技有限公司 | Developments blood pressure check device |
| CN110226926A (en) * | 2018-03-06 | 2019-09-13 | 罗伯特·博世有限公司 | For the calibration method of blood pressure device |
| CN112040854A (en) * | 2018-05-24 | 2020-12-04 | 欧姆龙健康医疗事业株式会社 | Blood pressure management device, blood pressure management method, and blood pressure management program |
| CN109893110A (en) * | 2019-03-06 | 2019-06-18 | 深圳市理邦精密仪器股份有限公司 | A kind of method and device for calibrating ambulatory blood pressure |
| CN112274126A (en) * | 2020-10-28 | 2021-01-29 | 河北工业大学 | Noninvasive continuous blood pressure detection method and device based on multiple pulse waves |
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